Point-Of-Interest (POI) recommendation not only assists users to find their preferred places, but also helps businesses to attract potential customers. Recent studies have proposed many approaches to the POI recommendation. However, the lack of negat...
Partial occlusion and background clutter in camera video surveillance affect the accuracy of video-based person re-identification (re-ID). To address these problems, we propose a person re-ID method based on random erasure of frame sampling and tempo...
An efficient method such as ranked set sampling is used for estimating the population parameters when the actual observation measurement is expensive and complicated. In this paper, we consider the problem of estimating the two-parameter xgamma (TPXG...
Mainstream numerical weather prediction (NWP) centers usually estimate the standard deviations of background error by using a randomization technique to calibrate specific parameters of the background error covariance model in variational data assimi...
Two key challenges in financial distress prediction are pronounced class imbalance between majority and minority classes and the persistent misclassification of hard-to-learn samples. To tackle these issues, this study proposes an ensemble framework...
Second-order Chebyshev–Edgeworth expansions are derived for various statistics from samples with random sample sizes, where the asymptotic laws are scale mixtures of the standard normal or chi-square distributions with scale mixing gamma or inverse e...
The present study aims to develop a random forest algorithm-based classifier to predict the occurrence of fire events using observed meteorological parameters a day in advance. We considered the skin temperature, the air temperature close to the surf...
Pain is a reliable indicator of health issues; it affects patients’ quality of life when not well managed. The current methods in the clinical application undergo biases and errors; moreover, such methods do not facilitate continuous pain monit...
This study focuses on improving healthcare quality by introducing an automated system that continuously monitors patient pain intensity. The system analyzes the Electrodermal Activity (EDA) sensor modality modality, compares the results obtained from...
Landslide hazards affect the security of human life and property. Mapping the spatial distribution of landslide hazard risk is critical for decision-makers to implement disaster prevention measures. This study aimed to predict and zone landslide haza...
Background: Male college students are at risk for weight gain due to unhealthy dietary habits. This study assessed the dietary habits of undergraduate college males. Methods: Online cross-sectional survey (n = 235) of randomly sampled male undergradu...
This investigation was designed to study the relationship between weight change over 10 years and leukocyte telomere length (LTL) in a large sample of 3070 randomly selected U.S. adults, 36–70 years old. The National Health and Nutrition Examin...
Link prediction is a fundamental problem for graphs, which can reveal the potential relationships between users. Graph embedding can easily encode graph structural relations, and heterogeneous attribute features in a continuous vector space, which is...
This proof-of-principle study analyzed fecal samples from 30 infants who participated in a randomized controlled trial on the effects of the macronutrient composition of infant formula on growth and energy balance. In that study, infants randomized t...
Mean–geometric mean (MGM) linking compares group differences on a latent variable
In order to reduce the number of calculations of the finite element model and the number of invocations of the implicit surrogate model in structural reliability analysis, an improved Monte Carlo reliability analysis method based on the Back Propagat...
Wireless body area networks (WBANs) for healthcare monitoring require age-of-information (AoI)-aware resource allocation under heterogeneous periodic and aperiodic traffic. Existing AoI-aware resource allocation methods can be broadly divided into ce...
The rationality of heavy vehicle models is crucial to the structural safety assessment of bridges. To establish a realistic heavy vehicle traffic flow model, this study proposes a heavy vehicle random traffic flow simulation method that fully conside...
In this paper, we carry out researches on randomized local binary features. Randomized local binary features have been used in many methods like RandomForests, RandomFerns, BRIEF, ORB and AKAZE to matching keypoints. However, in those existing method...
Federated learning is a distributed learning framework designed to protect user privacy, widely applied across various domains. However, existing federated learning algorithms face challenges, including slow convergence, significant loss fluctuations...
Surfactant-based drying of polymeric coatings is a highly non-linear complex process due to the involvement of simultaneous heat and mass transfer. It is quite challenging to model this type of system mathematically. We resorted to a data-driven tech...
The calibration method is used in stratified random sampling in the presence of measurement error to achieve optimum strata weights for better precision. In this study we attempt to analyze the behaviour of calibration estimators with different types...
This article completes our studies on the formal construction of asymptotic approximations for statistics based on a random number of observations. Second order Chebyshev–Edgeworth expansions of asymptotically normally or chi-squared distribute...
Background: Numerous observational studies have documented an association between the circadian rhythm and the composition of the gut microbiota. However, the bidirectional causal effect of the morning chronotype on the gut microbiota is unknown. Met...
The current study investigates the performance of various sampling designs in providing accurate estimates for crucial maize yield traits (intended for silage) including plant height, fresh/dry/ear weight, number of maize ears per plant, and total ea...
Background: Very few case reports have explored a potential link between ankylosing spondylitis (AS), an autoimmune disorder, and amyotrophic lateral sclerosis (ALS), a progressive neurodegenerative condition. We aimed to investigate whether genetic...
The problem that the randomly generated random projection matrix will lead to unstable classification results is addressed in this paper. To this end, a Tighter Random Projection-oriented entropy-weighted ensemble algorithm is proposed for classifyin...
Women with polycystic ovary syndrome (PCOS) have varying difficulties in achieving weight loss by lifestyle intervention, which may depend on adipose tissue metabolism. The objective was to study baseline subcutaneous adipose tissue gene expression a...
In order to improve the performance of the Kalman filter for nonlinear systems, this paper contains the advantages of UKF statistical sampling and EnKF random sampling, respectively, and establishes a new design method of sampling a driven Kalman fil...
The paper investigates the problem of performing a correlation analysis when the number of observations is large. In such a case, it is often necessary to combine random observations to achieve dimensionality reduction of the problem. A novel class o...
Declining gold discovery rates require prospectivity workflows that are statistically transparent at the regional scale, while remaining adaptable to project-scale geological interpretation. We present a robust sampled weights-of-evidence (sampled-Wo...
Techniques used in forensic analysis have to find an appropriate balance between fairness to the defendant and efficiency and safety for forensic personnel. Safety issues are particularly acute in analyzing large seizures of bags likely containing he...
Due to randomness factors in the machine learning model construction process, reproducibility is compromised. This study investigates the impact of randomness on model stability and evaluates techniques for reducing this impact using the widely adopt...
23 December 2021
Excessive weight gain and cardiometabolic dysfunction are common and clinically relevant side effects of antipsychotic medications. In this pilot study, we aimed to establish the feasibility of using metformin and its effectiveness in managing antips...
Background/Objectives: Recent Japanese guidelines recommend using the average sodium-to-potassium (Na/K) ratio from casual urine samples to assess hypertension and cardiovascular risk, suggesting cutoffs of 2 (optimal) and 4 (feasible). We aimed to e...
Rock drillability classification provides an important basis for drilling-parameter optimization, equipment selection, and improved mining efficiency. Existing drillability evaluation methods often rely on fixed empirical weights and rigid grade boun...
EISCAT VHF radar data are used for observing, monitoring, and understanding Earth’s upper atmosphere. This paper presents an approach to segment Polar Mesospheric Summer Echoes (PMSE) from datasets obtained from EISCAT VHF radar data. The data...
Leaf water content (LWC) is a key indicator of winter wheat water status, but the reliability of UAV hyperspectral and thermal infrared predictions varies across samples, limiting the effectiveness of fixed-weight fusion. To improve LWC estimation by...
Based on previous observational studies, the causal association between circulating adiponectin (CA) levels and ankylosing spondylitis (AS) risk remains unclear. Therefore, this study aims to investigate whether CA levels are related to the risk of A...
The increasing global prevalence of overweight and obesity highlights an urgent need to explore modifiable obesogenic factors. This study investigated the impact of lifestyle factors, such as beer and wine drinking, cigarette smoking, and leisure tim...
Based on the decoupled n-dodecane skeletal mechanism and the computational fluid dynamics (CFD) numerical framework, a multilayer feedforward neural network surrogate model was developed to predict ignition delay in a constant-volume combustion vesse...
While much evidence suggests that type 2 diabetes mellitus increases the risk of Parkinson’s disease (PD), the relationship between type 1 diabetes mellitus (T1DM) and PD is unclear. To study their association, we performed a two-sample Mendeli...
Research into the symbiotic relationship between plants and arbuscular mycorrhizal fungi (AMF) is key for sustainable agricultural intensification. The objective of the present study is to evaluate native AMF at the monosporic level in greenhouse-gro...
Non-probability samples are frequently used when a sampling frame is unavailable, or probability sampling is prohibitively costly, but naive estimates may be biased by selective participation. Most weighting research considers one non-probability sam...
Ranked set sampling (RSS) is a useful technique for improving the estimator of a population mean when the sampling units in a study can be more easily ranked than the actual measurement. RSS performs better than simple random sampling (SRS) when the...
Variational autoencoders (VAEs) are popular for their robust nonlinear representation capabilities and have recently achieved notable advancements in the problem of missing data imputation. However, existing imputation methods often exhibit instabili...
Non-landslide sample selection is critical in landslide susceptibility modeling due to its direct impact on model accuracy and reliability. This study compares three sample selection strategies: whole-region random selection, landslide buffer zone se...
Objective: Ankylosing spondylitis (AS) is associated with a variety of gut microbiotas. We aim to analyze the causal relationship between the two at the genetic level. Methods: Mendelian randomization (MR) is a type of instrumental variables (IVs) an...
Estimation of the standard radiation dose at each imaging facility is required for radiation dose management, including establishment and utilization of the diagnostic reference levels. We investigated methods to estimate the standard dose for pediat...
This article proposes a hybrid method for constructing composite indices in the context of decision-making through the integration of Uniform Manifold Approximation and Projection (UMAP) and the Random Forest algorithm. Unlike Principal Component Ana...
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